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Data codebook for: Ideological Cues, Partisanship, and Prejudice Against LGBTQ Judges

Andrew R. Stone (arstone@olemiss.edu) -- University of Mississippi
Tony Zirui Yang (zirui.yang@nuffield.ox.ac.uk) -- Emory University and Nuffield College, University of Oxford

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The analyses found in the paper and supplementary material can be replicated using the data found in survey_data_nominees_final.RData. The following variables are contained in the dataset.

ResponseId: Unique respondent identifier.
Education: Categorical variable capturing respondent education level (Some high school, or less; High school graduate or GED; Some college, no 4-year degree; College graduate; Post-graduate degree).
Income: Categorical variable capturing annual respondent household income (Less than $25,000; $25,000 to $50,000; $50,000 to $75,000; $75,000 to $100,000; $100,000 to $200,000; $200,000 or more).
Race: Categorical variable capturing respondent race; respondents were asked to select all categories that applied (White; Black or African American; Hispanic or Latino; Asian; American Indian or Alaska Native; Native Hawaiian or Pacific Islander; Other).
GenderIdentity: Categorical variable capturing respondent gender (Man; Woman; Transgender man; Transgender woman; Do not identify as man, woman, or transgender).
Sexuality: Categorical variable capturing respondent sexuality (Straight; Gay or lesbian; Bisexual; Do not identify as straight, gay or lesbian, or bisexual).
man: Binary measure for whether respondent is a cisgender man (1 is man, 0 is not).
transgender: Binary measure for whether respondent is transgender (1 is transgender, 0 is not).
gay_bisexual_other: Binary measure for whether respondent is gay, bisexual, or does not identify as straight/gay/bisexual (1 is gay/bisexual/not straight, gay, or bisexual, 0 is not).
college_degree: Binary measure for whether respondent has a college degree (1 is has college degree, 0 is does not).
income_over_75000: Binary measure for whether respondent has an annual household income over $75,000 (1 is yes, 0 is no).
white: Binary measure for whether respondent is white and no other racial group (1 is white and no other racial group, 0 is not).
knowledge4pt: Four-point measure of respondent factual knowledge of the Supreme Court as measured by additive index of four factual knowledge questions (ranges from 0 to 4 with higher values indicating higher knowledge).
judge_age: Factor denoting which age treatment the respondent received for that judge profile (45, 55, or 65).
judge_race: Factor denoting which race treatment the respondent received for that judge profile (Black, Asian, or Hispanic).
judge_law_school: Factor denoting which law school treatment the respondent received for that judge profile (Elite Ivy, Public, Not top 100).
judge_job: Factor denoting which current job treatment the respondent received for that judge profile (Judge, Public defender, Professor, Defense attorney).
judge_politics: Factor denoting which political views treatment the respondent received for that judge profile (Very liberal, Liberal, Somewhat liberal, Moderate).
judge_gender: Factor denoting which gender treatment the respondent received for that judge profile (Man, Transgender man, Woman, Transgender woman).
judge_transgender: Factor denoting whether respondent received a transgender treatment or not for that judge profile (Not transgender, Transgender).
judge_sexuality: Factor denoting which sexual orientation treatment the respondent received for that judge profile (Straight, Gay or lesbian).
judge_rhetoric: Factor denoting whether respondent received a Biden rhetoric treatment or not (No statement from Biden, Statement from Biden).
support_nominee: Binary measure of nominee support (1 is support, 0 is not).
support_nominee_5pt: Five-point measure of nominee support (5 is strongly support, 4 is somewhat support, 3 is neither oppose nor support, 2 is somewhat oppose, 1 is strongly oppose).
legitimacy_additive: Additive index of respondent evaluations of Court legitimacy (ranges from 0 to 5, higher values indicate greater legitimacy).
passed_attention: Binary measure for whether respondent gave a correct answer to our attention check (1 is correct, 0 is incorrect).
profile_evaluation: Denotes whether the respondent saw this nominee profile first or second.
Party: Factor denoting respondent partisanship, coding leaners as partisans.
True_Party: Factor denoting respondent partisanship, coding leaners as independents.
Ideology_3: Factor denoting respondent ideology with three levels (liberal, conservative, or moderate).
